Dr Tao Geng


NameDr Tao Geng
Job titleLecturer in Design Engineering
Research institute
Primary appointmentDesign Engineering & Mathematics
ORCIDhttps://orcid.org/0000-0002-6863-243X
Contact categoryAcademic staff (past)

Research outputs

The effect of swing leg retraction on biped walking stability is influenced by the walking speed and step-length

Bao, R. and Geng, T. 2018. The effect of swing leg retraction on biped walking stability is influenced by the walking speed and step-length. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain 01 - 05 Oct 2018 IEEE. pp. 3257-3262 https://doi.org/10.1109/IROS.2018.8593932

Fast walking with rhythmic sway of torso in a 2D passive ankle walker

Bao, R. and Geng, T. 2018. Fast walking with rhythmic sway of torso in a 2D passive ankle walker. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Madrid, Spain 01 - 05 Oct 2018 IEEE. pp. 4363-4368 https://doi.org/10.1109/IROS.2018.8593665

Wrist movement detector for ROS based control of the robotic hand

Krawczyk, M., Yang, Z., Gandhi, V., Karamanoglu, M., Franca, F., Priscila, L., Xiaochen, W. and Geng, T. 2018. Wrist movement detector for ROS based control of the robotic hand. Advances in Robotics & Automation. 7 (1). https://doi.org/10.4172/2168-9695.1000182

Using robot operating system (ROS) and single board computer to control bioloid robot motion

Kalyani, G., Yang, Z., Gandhi, V. and Geng, T. 2017. Using robot operating system (ROS) and single board computer to control bioloid robot motion. 18th Towards Autonomous Robotic Systems (TAROS) Conference. Guildford, Surrey, UK 19 - 21 Jul 2017 Springer. pp. 41-50 https://doi.org/10.1007/978-3-319-64107-2_4

ROS based autonomous control of a humanoid robot

Kalyani, G., Gandhi, V., Yang, Z. and Geng, T. 2016. ROS based autonomous control of a humanoid robot. 25th International Conference on Artificial Neural Networks (ICANN). Barcelona, Spain 06 - 09 Sep 2016 Springer. pp. 550-551 https://doi.org/10.1007/978-3-319-44778-0

Skins and sleeves for soft robotics: inspiration from nature and architecture

Lekakou, C., Elsayed, Y., Geng, T. and Saaj, C. 2015. Skins and sleeves for soft robotics: inspiration from nature and architecture. Advanced Engineering Materials. 17 (8), pp. 1180-1188. https://doi.org/10.1002/adem.201400406

A unified system identification approach for a class of pneumatically-driven soft actuators

Wang, X., Geng, T., Elsayed, Y., Saaj, C. and Lekakou, C. 2015. A unified system identification approach for a class of pneumatically-driven soft actuators. Robotics and Autonomous Systems. 63, pp. 136-149. https://doi.org/10.1016/j.robot.2014.08.017

Finite element analysis and design optimization of a pneumatically actuating silicone module for robotic surgery applications

Elsayed, Y., Vincensi, A., Lekakou, C., Geng, T., Saaj, C., Ranzani, T., Cianchetti, M. and Menciassi, A. 2014. Finite element analysis and design optimization of a pneumatically actuating silicone module for robotic surgery applications. Soft Robotics. 1 (4), pp. 255-262. https://doi.org/10.1089/soro.2014.0016

Torso inclination enables faster walking in a planar biped robot with passive ankles

Geng, T. 2014. Torso inclination enables faster walking in a planar biped robot with passive ankles. IEEE Transactions on Robotics. 30 (3), pp. 753-758. https://doi.org/10.1109/TRO.2014.2298058

Online regulation of the walking speed of a planar limit cycle walker via model predictive control

Geng, T. 2014. Online regulation of the walking speed of a planar limit cycle walker via model predictive control. IEEE Transactions on Industrial Electronics. 61 (5), pp. 2326-2333. https://doi.org/10.1109/TIE.2013.2272274

Synergy-based affordance learning for robotic grasping

Geng, T., Wilson, J., Sheldon, M., Lee, M. and Hülse, M. 2013. Synergy-based affordance learning for robotic grasping. Robotics and Autonomous Systems. 61 (12), pp. 1626-1640. https://doi.org/10.1016/j.robot.2013.07.002

Transferring human grasping synergies to a robot

Geng, T., Lee, M. and Hülse, M. 2011. Transferring human grasping synergies to a robot. Mechatronics. 21 (1), pp. 272-284. https://doi.org/10.1016/j.mechatronics.2010.11.003

A self-paced online BCI for mobile robot control

Geng, T., Gan, J. and Hu, H. 2010. A self-paced online BCI for mobile robot control. International Journal of Advanced Mechatronic Systems. 2 (1/2), p. 28. https://doi.org/10.1504/IJAMECHS.2010.030846

Planar biped walking with an equilibrium point controller and state machines

Geng, T. and Gan, J. 2010. Planar biped walking with an equilibrium point controller and state machines. IEEE/ASME transactions on mechatronics. 15 (2), pp. 253-260. https://doi.org/10.1109/TMECH.2009.2024742

A novel design of 4-class BCI using two binary classifiers and parallel mental tasks

Geng, T., Gan, J., Dyson, M., Tsui, C. and Sepulveda, F. 2008. A novel design of 4-class BCI using two binary classifiers and parallel mental tasks. Computational Intelligence and Neuroscience. 2008, pp. 1-5. https://doi.org/10.1155/2008/437306

Adaptive, fast walking in a biped robot under neuronal control and learning

Manoonpong, P., Geng, T., Kulvicius, T., Porr, B. and Wörgötter, F. 2007. Adaptive, fast walking in a biped robot under neuronal control and learning. PLoS Computational Biology. 3 (7), p. e134. https://doi.org/10.1371/journal.pcbi.0030134

A reflexive neural network for dynamic biped walking control

Geng, T., Porr, B. and Wörgötter, F. 2006. A reflexive neural network for dynamic biped walking control. Neural Computation. 18 (5), pp. 1156-1196. https://doi.org/10.1162/089976606776241057

Fast biped walking with a sensor-driven neuronal controller and real-time online learning

Geng, T. 2006. Fast biped walking with a sensor-driven neuronal controller and real-time online learning. The International Journal of Robotics Research. 25 (3), pp. 243-259. https://doi.org/10.1177/0278364906063822

Dynamics and trajectory planning of a planar flipping robot

Geng, T. 2005. Dynamics and trajectory planning of a planar flipping robot. Mechanics Research Communications. 32 (6), pp. 636-644. https://doi.org/10.1016/j.mechrescom.2004.06.009
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